A spatio-temporal analysis of the impact of congestion on traffic safety on major roads in the UK

A spatio-temporal analysis has been conducted aiming to explore the relationship between traffic congestion and road accidents based on the data on the M25 motorway and its surrounding major roads in England during the period 2003-2007. It was hypothesised that increased traffic congestion may be beneficial to road safety as the number of fatal and serious injury (KSI) accidents would be less due to low average speed when congestion is present. If this is confirmed then it poses a potential dilemma for transport policy makers. A series of classical count outcome models (random-effects Negative Binomial models) and spatial models using a full Bayesian hierarchical approach have been developed in this study in order to examine whether congestion has any effect on the frequency of accidents. The results suggest that increased traffic congestion is associated with more KSI accidents and traffic congestion has little impact on slight injury accidents. This may be due to the higher speed variance among vehicles within and between lanes and worse driving behaviour in the presence of congestion. In addition, traffic speeds even within congested situations are likely to be relatively high on major roads compared to other parts of the road network. Some strategies are then proposed to optimise traffic flow which would be beneficial to both congestion and accident reduction

The effects of area-wide road speed and curvature on traffic casualties in England

Transport provides a range of benefits to society in terms of mobility, access and economic growth. There are however negative impacts of transport, not least in terms of environmental degradation, damage to property, traffic accidents and loss of life. This paper focuses on road traffic accidents, the reduction of which is an important aim of transport policy world wide. The primary objective of this paper is to develop a series of relationships using spatially disaggregated area-level cross-sectional data between different traffic casualties, road traffic speed and road curvature by controlling for other contributing factors associated with area characteristics. The spatial units of the analysis are the 8019 census wards in England. Ward-level casualty data are disaggregated by severity of the casualty (such as fatalities, serious injuries and slight injuries) and by the severity of the casualty related to various road users. The results suggest that increased average speed within a ward is positively associated with total fatalities and serious injuries; and road curvature is found to be negatively associated with road accidents

Multilevel modelling of Demand Responsive Transport (DRT) trips in Greater Manchester based on area-wide socio-economic data

Providing public transport in areas of low demand has long proved to be a challenge to policy makers and practitioners. With the developing economic, social and environmental trends, there is pressure for alternative solutions to the policy of subsidising conventional bus services. One potential solution is to adopt more flexible routes and/or timetables to better match the required demand. Therefore such 'on demand' or 'Demand Responsive Transport' (DRT) services (known as paratransit in the US) have been adopted in a number of locations. This paper seeks to explore the effects of area-wide factors on the demand of DRT by reporting the results of a statistical analysis of DRT service provision in the metropolitan region of Greater Manchester, the public transport authority of which offers one of the largest and most diverse range of DRT schemes in the UK. Specifically, this paper employs a multilevel modelling approach to investigate the impact of both DRT supply-oriented factors at the service area level and socio-economic factors at the lower super output area (LSOA) level on the average number of trips made by DRT per year. This hierarchical or 'nested' structure was adopted because typically the LSOAs within the same Service Area may share similar characteristics. It is found that the demand for DRT services was higher in areas with low car ownership, low population density, high proportion of white people, and high levels of social deprivation, measured in terms of income, employment, education, housing and services, health and disability, and living environment. © 2013 The Author(s)

Photoelectrochemical cell for simultaneous electricity generation and heavy metals recovery from wastewater

The feasibility of simultaneous recovery of heavy metals from wastewater (e.g., acid mining and electroplating) and production of electricity is demonstrated in a novel photoelectrochemical cell (PEC). The photoanode of the cell bears a nanoparticulate titania (TiO2) film capped with the block copolymer [poly(ethylene glycol)-b-poly(propylene glycol)-b-poly(ethylene glycol)] hole scavenger, which consumed photogenerated holes, while the photogenerated electrons transferred to a copper cathode reducing dissolved metal ions and produced electricity. Dissolved silver Ag+, copper Cu2+, hexavalent chromium as dichromate Cr2O72− and lead Pb2+ ions in a mixture (0.2 mM each) were removed at different rates, according to their reduction potentials. Reduced Ag+, Cu2+ and Pb2+ ions produced metal deposits on the cathode electrode which were mechanically recovered, while Cr2O72− reduced to the less toxic Cr3+ in solution. The cell produced a current density Jsc of 0.23 mA/cm2, an open circuit voltage Voc of 0.63 V and a maximum power density of 0.084 mW/cm2. A satisfactory performance of this PEC for the treatment of lead-acid battery wastewater was observed. The cathodic reduction of heavy metals was limited by the rate of electron-hole generation at the photoanode. The PEC performance decreased by 30% after 9 consecutive runs, caused by the photoanode progressive degradation

Mechanism and experimental study on the photocatalytic performance of Ag/AgCl @ chiral TiO2 nanofibers photocatalyst: the impact of wastewater components

© 2014 Elsevier B.V.The effect of the water matrix components of a secondary effluent of a urban wastewater treatment plant on the photocatalytic activity of Ag/AgCl @ chiral TiO2 nanofibers and the undergoing reaction mechanisms were investigated. These effects were evaluated through the water components-induced changes on the net rate of hydroxyl radical (•OH) generation and modeled using a relative rate technique. Dissolved organic matter DOM (k=-2.8×108M-1s-1) scavenged reactive oxygen species, Cl- (k=-5.3×108M-1s-1) accelerated the transformation from Ag to AgCl (which is not photocatalytically active under visible-light irradiation), while Ca2+ at concentrations higher than 50mM (k=-1.3×109M-1s-1) induced aggregation of Ag/AgCl and thus all of them revealed inhibitory effects. In contrast, NO3- (k=6.9×108M-1s-1) and CO32- (k=3.7×108M-1s-1) improved the photocatalytic activity of Ag/AgCl slightly by improving the rate of HO• generation. Other ubiquitous secondary effluent components including SO42- (k=3.9×105M-1s-1), NH3+ (k=3.5×105M-1s-1) and Na+ (k=2.6×104M-1s-1) had negligible effects. 90% of 17-α-ethynylestradiol (EE2) spiked in the secondary effluent was removed within 12min, while the structure and size of Ag/AgCl @ chiral TiO2 nanofibers remained stable. This work may be helpful not only to uncover the photocatalytic mechanism of Ag/AgCl based photocatalyst but also to elucidate the transformation and transportation of Ag and AgCl in natural water

Quantifying the transport-related impacts of parental school choice in England

School travel is becoming increasingly car-based and this is leading to many environmental and health implications for children all over the world. One of several reasons for this is that journey to school distances have increased over time. This is a trend that has been reinforced in some countries by the adoption of so-called ‘school choice’ policies, whereby parents can apply on behalf of their child(ren) to attend any school, and not only the school they live closest to. This paper examines the traffic and environmental impacts of the school choice policy in England. It achieves this by analysing School Census data from 2009 from the Department for Education. Multinomial logit modelling and mixed multinomial logit modelling are used to illustrate the current travel behaviour of English children in their journey to school and examine how there can be a significant reduction in vehicle miles travelled, CO2 emissions and fuel consumption if the ‘school choice’ policy is removed. The model shows that when school choice was replaced by a policy where each child only travelled to their ‘nearest school’ several changes occurred in English school travel. Vehicle Miles Travelled (VMT) by motorised transport fell by 1 % for car travel and 10 % for bus travel per day. The reduction in vehicle miles travelled could lead to less congestion on the roads during the morning rush hour and less cars driving near school gates. Mode choice changed in the modelled scenario. Car use fell from 32 to 22 %. Bus use fell from 12 to 7 %, whilst NMT saw a rise of 17 %. With more children travelling to school by walking or cycling the current epidemic of childhood obesity could also be reduced through active travel

Histogram of BREAST data.

In this study, tests of fit for the power function lognormal distribution is considered. The probability plot, probability plot correlation coefficient, and goodness-of-fit tests—the Kolmogorov–Smirnov (KS), Cramér–von Mises (CvM), and Anderson–Darling (AD) tests are provided. Tables of critical values are presented by using simulation techniques, and the AD test outperforms KS and CvM tests based on power comparisons. Finally, to illustrate these test procedures, we fit this distribution to the data which represent the survival times of 121 breast cancer patients from one hospital.</div

Tests and associated p–values for BREAST data.

In this study, tests of fit for the power function lognormal distribution is considered. The probability plot, probability plot correlation coefficient, and goodness-of-fit tests—the Kolmogorov–Smirnov (KS), Cramér–von Mises (CvM), and Anderson–Darling (AD) tests are provided. Tables of critical values are presented by using simulation techniques, and the AD test outperforms KS and CvM tests based on power comparisons. Finally, to illustrate these test procedures, we fit this distribution to the data which represent the survival times of 121 breast cancer patients from one hospital.</div

Critical values of Anderson–Darling test statistic <i>A</i>².

Critical values of Anderson–Darling test statistic A2.</p

Empirical and fitted PDFs for BREAST data.

In this study, tests of fit for the power function lognormal distribution is considered. The probability plot, probability plot correlation coefficient, and goodness-of-fit tests—the Kolmogorov–Smirnov (KS), Cramér–von Mises (CvM), and Anderson–Darling (AD) tests are provided. Tables of critical values are presented by using simulation techniques, and the AD test outperforms KS and CvM tests based on power comparisons. Finally, to illustrate these test procedures, we fit this distribution to the data which represent the survival times of 121 breast cancer patients from one hospital.</div